This plot shows the pipeline performance overview. Some metrics are calculated.

• Heatmap score[Contaminants]: as fraction of summed intensity with 0 = sample full of contaminants; 1 = no contaminants
• Heatmap score[Pep Intensity (>23.0)]: Linear scale of the median intensity reaching the threshold, i.e. reaching 221 of 223 gives score 0.25.
• Heatmap score[Charge]: Deviation of the charge 2 proportion from a representative Raw file.
• Heatmap score [MC]: the fraction (0% - 100%) of fully cleaved peptides per Raw file
• Heatmap score [MC Var]: each Raw file is scored for its deviation from the ‘average’ digestion state of the current study.
• Heatmap score [ID rate over RT]: Scored using ‘Uniform’ scoring function.
• Heatmap score [MS2 Oversampling]: The percentage of non-oversampled 3D-peaks.
• Heatmap score [Pep Missing]: Linear scale of the fraction of missing peptides.

This plot shows the Proteomics Experimental Design. You can see details about it in https://abibuilder.informatik.uni-tuebingen.de/archive/openms/Documentation/release/latest/html/classOpenMS_1_1ExperimentalDesign.html

This plot shows the ProteomicsLFQ pipeline summary statistics

This plot shows the ProteomicsLFQ pipeline final result. Including Sample Name、Possible Study Variables、identified the number of peptide in the pipeline、 and identified the number of modified peptide in the pipeline, eg. All data in this table are obtained from the out_msstats file. You can also remove the decoy with the remove_decoy parameter.

This statistic is extracted from the out_msstats file. Proteins supported by more peptide identifications can constitute more confident results.

The quantification information of peptides is obtained from the pep table in the mzTab file. The table shows the quantitative level of peptides in different study variables.